Digital images are often plagued with noise such as artifacts and other degradations. For many different applications, one wants to remove the noise and enhance the image so as to bring out features of the image while at the same time suppressing noise and other artifacts that in general degrade the image. Accordingly, a variety of image enhancement techniques have been developed.
One such technique is the so-called Wiener filtering technique which is a method that involves taking a Fourier transform of an image and generating a linear filter function to modify the Fourier transform coefficients by either increasing them or decreasing them at every frequency.
Limitations in this method have lead to the development of other visual enhancement techniques. For example, U.S. Pat. No. 5,526,446 to Adelson et. al. describes a method to enhance digital images by converting an image into a set of coefficients in a multi-scale image decomposition process, followed by modification of each coefficient based on its value and the value of coefficients of related orientation, position, or scale, which is in turn followed by a reconstruction or synthesis process to generate the enhanced image.
However, a need still exists for an image enhancement technique that improves image quality and achieves faster image processing performance than known image enhancing techniques.